CN101501515B - Obtaining test data for a device - Google Patents
Obtaining test data for a device Download PDFInfo
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- CN101501515B CN101501515B CN2006800286534A CN200680028653A CN101501515B CN 101501515 B CN101501515 B CN 101501515B CN 2006800286534 A CN2006800286534 A CN 2006800286534A CN 200680028653 A CN200680028653 A CN 200680028653A CN 101501515 B CN101501515 B CN 101501515B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/28—Testing of electronic circuits, e.g. by signal tracer
- G01R31/317—Testing of digital circuits
- G01R31/31708—Analysis of signal quality
- G01R31/31711—Evaluation methods, e.g. shmoo plots
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/28—Testing of electronic circuits, e.g. by signal tracer
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/22—Detection or location of defective computer hardware by testing during standby operation or during idle time, e.g. start-up testing
- G06F11/26—Functional testing
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- G—PHYSICS
- G11—INFORMATION STORAGE
- G11C—STATIC STORES
- G11C29/00—Checking stores for correct operation ; Subsequent repair; Testing stores during standby or offline operation
- G11C29/04—Detection or location of defective memory elements, e.g. cell constructio details, timing of test signals
- G11C29/08—Functional testing, e.g. testing during refresh, power-on self testing [POST] or distributed testing
- G11C29/10—Test algorithms, e.g. memory scan [MScan] algorithms; Test patterns, e.g. checkerboard patterns
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- G—PHYSICS
- G11—INFORMATION STORAGE
- G11C—STATIC STORES
- G11C29/00—Checking stores for correct operation ; Subsequent repair; Testing stores during standby or offline operation
- G11C29/56—External testing equipment for static stores, e.g. automatic test equipment [ATE]; Interfaces therefor
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- G—PHYSICS
- G11—INFORMATION STORAGE
- G11C—STATIC STORES
- G11C29/00—Checking stores for correct operation ; Subsequent repair; Testing stores during standby or offline operation
- G11C29/56—External testing equipment for static stores, e.g. automatic test equipment [ATE]; Interfaces therefor
- G11C29/56004—Pattern generation
Abstract
Obtaining test data for a device under test includes obtaining a first part of the test data by testing the device at first points of a range of parameters using progressive sampling, and obtaining a second part of the test data by testing the device at second points of the range of parameters using adaptive sampling.
Description
Cross reference
Present patent application requires the U.S. Provisional Application No.60/705 in submission on August 4th, 2005,639 right of priority, and this provisional application is included in this application by reference, as here illustrating.
Technical field
Present patent application is usually directed to the test data of acquisition device, and relates more specifically to adopt progressive and adaptively sampled this test data of obtaining.
Background technology
The performance of semiconductor devices may change with the variation of many different operating parameters.For throughput rate and the profit that improves new unit, wish at first to check for the production of this device and the manufacturing process of producing reliably device stable in the operating conditions scope of expectation.Below also be useful: carry out quality control at production period, so that the sub-fraction device is sampled, thereby guarantee that manufacture process produces stable device in the operating conditions scope of expectation continuously.Can check the measuring technology of the stability of device in certain condition and range to be commonly referred to " shmoo " or " shmoo figure ".
Even shmoo figure can be one dimension, two dimension, three-dimensional N dimension.Every dimension of shmoo figure represents the device parameters that one or more is variable.These device parameters can comprise: device power source voltage (V
Dd), device clock frequency/cycle and numeral input or output voltage.Yet, can utilize the random devices parameter to check the operation of this device or identification about the problem of this device.
Can obtain such as the test data for generation of the test data of shmoo figure by ATE (automatic test equipment) (ATE).ATE is the automatic system that is used for test such as semiconductor, electronic circuit and printed circuit-board assembly of computer drives normally.Device by the ATE test is called as measured device (DUT).
Summary of the invention
Present patent application has been described and has been used for utilizing the progressive and adaptively sampled equipment that obtains the method for test data and comprise computer program.
Usually, according to an aspect, the objective of the invention is to obtain the test data of measured device, the test data of obtaining measured device comprises: locate to test this device by utilizing in parameter area first of progressive sampling, obtain the first of this test data; And by utilizing adaptively sampled second point place in this parameter area to test this device, obtain the second portion of this test data.This aspect of the present invention can also comprise one or more feature that the following describes.
The first that obtains this test data comprises: determine whether first quantity in this group surpasses threshold value.If first quantity surpasses described threshold value in should group, then this aspect can comprise and repeats progressive sampling, tests and carry out interpolation.If this quantity of first surpasses this threshold value, then can obtain the second portion of this test data.The second portion that obtains this test data comprises: carry out in this test data adaptively sampled, to identify one group of second point; Test this device to produce the second test result at this group second point place; And utilize the second test result to carry out interpolation to produce the part of this test data.The second portion that obtains this test data can also comprise: arrange and adaptively sampled relevant measuring; Determine on test data, whether to exist and satisfy the annex point that this is measured; Carry out adaptively sampled with another group second point of identification from these annex points in this test data; Test this device to produce additional the second test result at another group second point place; And utilize this additional second test result to carry out interpolation to produce the part of this test data.
Above-mentioned aspect can also comprise: specify the parameter of definition test data, wherein this test data can comprise a plurality of points, and these a plurality of points comprise first group and the group of second point; A plurality of points of a predetermined level is exceeded have been determined whether after tested.If also do not test a plurality of points of a predetermined level is exceeded, then this aspect can also comprise by thirdly locating to test the third part that this device obtains this test data in this test data of utilizing progressive sampling identification.Can utilize the first of this test data and second portion to carry out interpolation obtaining the disappearance part of this test data, and can utilize this first and second portion and this disappearance part to show this test data.
Progressive sampling can comprise with basically uniformly this test data of profile samples to obtain the first point.Sample this test data to obtain second point adaptively sampled can comprising according to the point of previous test data of sampling.This test data can comprise the grid with the first peacekeeping second dimension, wherein first tie up corresponding to first parameter relevant with this device, and the second dimension is corresponding to second parameter relevant with this device.Test can be included in the situation of given this second parameter and obtain this first parameter, perhaps obtains this second parameter in the situation of given this first parameter.This device can comprise semiconductor devices, and this test data can be represented as shmoo figure.
Accompanying drawing and following description describe one or more example in detail.According to this description and accompanying drawing and claims, other features of the present invention, aspect and advantage are apparent.
Description of drawings
Fig. 1 to 3 illustrates the example of shmoo figure.
Fig. 4 is the block scheme for the ATE of test component.
Fig. 5 is the block scheme for the tester of ATE.
Fig. 6 a to 6e illustrates and utilizes pixel to copy the stage that interpolation is carried out progressive sampling.
Fig. 7 a to 7c illustrates the stage of utilizing the sub sampling to carry out progressive sampling.
Fig. 8 illustrates the process for generation of shmoo figure.
Fig. 9 a to 9c illustrates 3 stages of the shmoo figure of the Fig. 1 that utilizes progressive self-adaptation grid sampling generation.
Figure 10 a to 10c illustrates 3 stages of the shmoo figure of the Fig. 1 that utilizes progressive self-adapting random sampling generation.
Figure 11 a to 11c illustrates 3 stages of the shmoo figure of the Fig. 2 that utilizes progressive self-adaptation grid sampling generation.
Figure 12 a to 12c illustrates 3 stages of the shmoo figure of the Fig. 2 that utilizes progressive self-adapting random sampling generation.
Figure 13 a to 13f illustrates the stages of the shmoo figure of the Fig. 3 that utilizes progressive self-adaptation grid sampling generation.
Figure 14 a to 14f illustrates the stages of the shmoo figure of the Fig. 3 that utilizes progressive self-adapting random sampling generation.
Figure 15 illustrates the example of the shmoo figure with different size feature.
Figure 16 a to 16c illustrates 3 stages of the shmoo figure of the Figure 15 that utilizes progressive self-adaptation grid sampling generation.
Figure 17 a to 17c illustrates 3 stages of the shmoo figure of the Figure 15 that utilizes progressive self-adapting random sampling generation.
In different accompanying drawings, same Ref. No. represents identical element.
Embodiment
At this a kind of method of the test data be used to obtaining measured device has been described.The method comprises: locate to test this device to obtain the first of this test data by utilizing progressive sampling first of parameter area; And by utilizing adaptively sampled second point place at parameter area to test this device to obtain the second portion of this test data.In the situation that produces the shmoo figure of shmoo figure shown in accompanying drawing, described the method, yet the present invention is not limited to producing shmoo figure and uses.But, can utilize method described here to obtain test data from random devices, and represent in any way this test data.
Fig. 1 to 3 illustrates the example of shmoo figure.Fig. 1 illustrates V
DdThe shmoo figure of (device power source voltage) and device clock period Relations Among.Fig. 2 illustrates V
OlThe shmoo figure of (digital pin output voltage) and device clock period relation.Shmoo figure shown in Fig. 1 and 2 is two-dimentional shmoo figure, and wherein when each place, point of crossing of parameter value went out qualified/defective result for the thermometrically of this device, two device parameters changed.Shmoo figure can also be gray level.Fig. 3 illustrates the shmoo figure of " eye pattern ", wherein, tests simultaneously and draw the result of 8 device pins.Whole 8 pins of white expression all pass through to test, and black represents whole 8 pins all by test, and grey represents that other pins do not pass through test to some pins by test.
With reference to figure 4, the system 10 that is used for the measured device (DUT) 18 of test such as semiconductor devices comprises the tester 12 such as ATE (automatic test equipment) (ATE) or other similar testing apparatuss.In order to control tester 12, system 10 comprises by hardware connection 16 computer systems 14 that are connected with tester 12 interfaces.Usually, computer system 14 sends to the tester 12 that the starting routine is carried out and is used for the function of test DUT18 with order.This execution test routine can start the generation of test signal and to the transmission of DUT18 and for the collection from the response of this DUT.Can utilize the various types of DUT of system's 10 tests.For example, DUT can be the semiconductor devices such as integrated circuit (IC) chip (such as storage chip, microprocessor, analog to digital converter, digital to analog converter etc.).
In order test signal to be delivered to this DUT and to be gathered response from this DUT, tester 12 is connected to one or more connector pinout, and this connector pinout is provided for the interface of the internal circuit of DUT18.In order to test some DUT, for example, 64 or 128 (perhaps more) connector pinouts of as many as can be connected to tester 12 by interface.In order to say something, in this embodiment, connect by rigid line, semiconductor device tester 12 is connected to the connector pinout of DUT18.Conductor 20 (for example cable) is connected to pin 22, and is used to test signal (such as PMU test signal, PE test signal etc.) is sent to the internal circuit of DUT18.Conductor 20 also comes at pin 22 place's detection signals in response to the test signal that is provided by semiconductor device tester 12.For example, the response test signal is at pin 22 place's detectable voltage signals or current signals, then by conductor 20 this voltage signal or current signal is sent to tester 12 and analyzes.Can also carry out this single port test by other pins in being included in DUT18.For example, tester 12 can be provided to test signal in other pins, then gathers the coherent signal that reflects by conductor (signal that provides is provided).By gathering reflected signal, together with the input impedance of all right characterization (characterize) pin of other single port test volumes.Under other test case, can digital signal be sent to pin 22 by conductor 20, so that digital value is stored on the DUT18.In case finish storage, just can access DUT18, send to tester 12 with the digital value of retrieving this storage and by the digital value that conductor 20 will be stored.Then, identify this key numbers value to determine whether right value is stored on the DUT18.
Measure except carrying out single port, can also utilize semiconductor device tester 12 to carry out the dual-port test.For example, can test signal be injected pin 22 by conductor 20, and can gather response signal from one or more other pins of DUT18.This response signal can be provided to semiconductor device tester 12 to determine the quantity such as gain response, phase response and other handling capacities (throughout) measuring amount.
Also with reference to figure 5, in order to send test massage and to gather test signal from a plurality of connector pinouts of DUT (perhaps a plurality of DUT), semiconductor device tester 12 comprises the interface card 24 that can communicate by letter with many pins.For example, interface card 24 can be sent to test signal for example 32,64 or 128 pins, and gathers corresponding response.Each communication link to pin is commonly called channel, and by test signal is provided to large volumes of channels, so shortened the test duration because can carry out simultaneously a plurality of tests.Except having at interface card a plurality of channels, can increase a plurality of interface cards the sum of channel, thereby further shorten the test duration by in tester 12, comprising.In this embodiment, 2 additional interface cards 26 and 28 are shown to show that a plurality of interface cards can be installed on the tester 12.
Each interface card comprises for special IC (IC) chip (for example application-specific IC (ASIC)) of carrying out particular test functionality.For example, interface card 24 comprises the IC chip 30 for execution parameter measuring unit (PMU) test and pin electronic (PE) test.IC chip 30 has: PMU level 32 comprises be used to the circuit that carries out the PMU test; And PE level 34, comprise be used to the circuit that carries out the PE test.In addition, interface card 26 and 28 comprises respectively the IC chip 36 and 38 with PMU and PE circuit.Usually, PMU test comprises DC voltage or current signal is offered DUT to determine the amount such as the DC performance characteristic of input and output impedance, current leakage and other types.PE test comprises AC test signals and waveform is sent to DUT (for example DUT18) and gather response with the performance of further this DUT of characterization.For example, IC chip 30 can will represent that the AC test signals for the vector that is stored in the binary value on the DUT sends to this DUT.In case stored these binary values, tester 12 just can be accessed this DUT to determine whether to have stored correct binary value.Because digital signal generally includes abrupt voltage transitions, so compare with the circuit in the PMU level 32, the Circuits System in the PE level 34 on the IC chip 30 is with relatively high speed operation.
For direct current and AC test signals and analog waveform are sent to DUT18 from interface card 24, conductive trace 40 is connected to interface card connector 42 with IC chip 30, and this interface card connector 42 allows signals to be sent to interface card 24 and transmits signals from interface card 24.Interface card connector 42 is also connected to the connector 44 that links to each other with interface connector 46, the signal that this interface connector 46 allows signal to be sent to tester 12 and to send self-test device 12.In this embodiment, conductor 20 is connected to interface connector 46, to realize the two-way signaling transmission between the pin 22 of tester 12 and DUT18.In some are arranged, can utilize interface arrangement that one or more conductor is connected to this DUT from tester 12.For example, this DUT (for example DUT18) can be installed in device interface card (DIB) upward to access each DUT pin.In this layout, conductor 20 can be connected to DIB with on (a plurality of) the correct pin (for example pin 22) that test signal is applied to this DUT.
In this embodiment, only conductive trace 40 is connected with conductor and is connected respectively IC chip 30 and interface card 24, to transmit and collection signal.Yet, IC chip 30 (and IC chip 36 and 38) has a plurality of pins (such as 8,16 etc.) usually, and these pins link to each other to provide signal with a plurality of conductive traces respectively and gather signal from DUT (passing through DIB) with respective conductors.In addition, in some were arranged, tester 12 can be connected to two or more DIB being connected to one or more measured device by interface card 24,26 and 28 channel interfaces that provide.
In order to start and to control by interface card 24,26 and 28 tests of carrying out, tester 12 comprises PMU control circuit 48 and the PE control circuit 50 that is provided for producing test signal and analyzes the test parameter (such as test signal voltage level, current test signal level, digital value etc.) of DUT response.PMU control circuit 48 and PE control circuit 50 can be the parts of one or more IC, also can utilize such as the treating apparatus of digital signal processor (DSP) and realize.Tester 12 also comprises computer interface 52, and the transmission of data between tester 12 and computer system 14 (such as test parameter, DUT response etc.) is controlled and allowed in the operation that this computer interface 52 allows 14 pairs of testers of computer system 12 to carry out.
According to process described here, computer system 14 is obtained test result from tester 12.In this embodiment, according to these test results, this process produces one or more shmoo figure, yet, the expression that can produce other types.This expression can be identical with the situation of shmoo figure is figure, can not be figure also.Procedure division described here ground is based on progressive and adaptively sampled technology.In brief, this process is included in first of utilizing in the parameter area that progressive sampling identifies and locates to test the first that this device obtains test data; And by testing the second portion that this device obtains this test data at the second point place that utilizes the adaptively sampled parameter area of identifying.The second portion of this test data can comprise the data of this first's disappearance.The below will begin to do and be described in more detail from describing progressive sampling and adaptively sampled technology.
Developed progressive sampling as so a kind of method, thereby it sends digital picture so that show fast the low resolution version of this image by the slow data path, and then along with the increasing view data of transmission incrementally improves picture quality.A kind of progressive sampling that is called as grid sampling on coarse grid to image sampling, then, by sampled pixel being copied and copies to the right side downwards filling the pixel of disappearance, thereby to the residual pixel interpolation.Then, carry out the next stage of progressive sampling with the twice of previous raster resolution, and utilize identical pixel reproduction technology to come interpolation.Carry out this process continuously until all pixels of having sampled.Fig. 6 a to 6e is illustrated in each stage of the such progressive sampling in the shmoo figure situation shown in Figure 1.Can outside the situation of shmoo figure, carry out progressive sampling.
Shown in Fig. 6 a to 6e, progressive grid sampling has four times of sampled point in each successive stages to produce the next stage grid.If require less progressive increment, then the stage shown in Fig. 6 a to 6e can be divided into 3 less subs.Fig. 7 a to 7c illustrates how be divided into 3 less subs the stage shown in Fig. 6 b.(Fig. 7 a) samples and is positioned at the point at previous grid center the first sub.The point of the vertical centre between the point of the second sub (Fig. 7 b) sampling in previous grid.The point at the horizontal center between the point of the 3rd sub (Fig. 7 c) sampling in previous grid.
For preferred sampling has the target of the point of the more information content, adaptively sampled point take previous sampling is selected the point that then will sample as the basis.In shmoo figure, information is usually along passing through/not concentrating by changing.Therefore, in the situation of shmoo, adaptively sampled concentrate on by/by on changing.May not so in other cases.
Fig. 8 illustrates the progressive and adaptively sampled process 60 of obtaining test data that adopts.Note that in shmoo figure situation and describe process 60, yet under any circumstance implementation 60 is obtained test data, and can utilize figure or also can not utilize this test data of diagrammatic representation.In addition, although described process 60 here in two-dimentional plot situation, process 60 can be applied to the shmoo figure (being the arbitrary parameter scope) of Arbitrary Dimensions.
Process 60 with specify (61) definition shmoo figure such as V
Dd, the parameter of clock period etc. and requirement the resolution of shmoo figure begin.Process 60 is carried out progressive (approximately) uniform sampling of (62) shmoo figure, (64) point of the predetermined quantity among the shmoo figure until sample.At each sampled point, carry out (63) device detection.Process 60 receives this test result and test result is incorporated in the sampled point of shmoo figure.For example, if at specific V
DdValue and specific clock period are located to test, and then processing procedure 60 is upgraded shmoo figure to reflect that test result is for example by (white) or by (black).
After each stage of progressive uniform sampling, process 60 is utilized from the test data of sampled point acquisition and is carried out interpolation at shmoo figure, to obtain the missing point of this shmoo figure.In non-shmoo figure situation, can only carry out interpolation with interpolation from from the test data that obtains test data.After this, and the interpolation shmoo figure that process 60 demonstrations (66) obtain (perhaps other expressions, as the case may be).In case utilize progressive sampling (64) point more than the scheduled volume (for example number percent) at shmoo figure up-sampling, then process 60 switches to and utilizes interpolation shmoo figure to carry out adaptively sampled.
Also carry out stage by stage adaptively sampled.By proceeding progressive uniform sampling, can select (67) sampling candidate point, yet, in fact, in fact do not sample have a few.Determine whether the sampling set point by evaluation module.Evaluation module is that each the non-sampled point definition among the shmoo figure is measured.Can be according to determining that from the interpolation shmoo figure that is right after sample phase the preceding this measures.If this is measured above predetermined threshold (69), then utilize this point of adaptively sampled sampling the (70).That is, carry out device detection in each sample point.Process 60 receives these test results and test result is incorporated into shmoo figure that (perhaps other expressions are in the sampled point as the case may be).
Adaptively sampled stage one finishes, and process 60 is just carried out interpolation (65) obtaining the missing point of shmoo figure, and process 60 shows the interpolation shmoo figure that (66) obtain.Explain that as above in non-shmoo figure situation, process 60 is only carried out interpolation (65) to obtain missing data.After this, can utilize the interpolation shmoo figure that obtains as baseline, carry out adaptively sampled next stage.Measure at this point and to be no more than this threshold value (69), sampled greater than the scheduled volume (72) of shmoo figure and not in the situation of sample a little (74), process 60 is carried out the additional phase of progressive uniform sampling, then returns adaptively sampled.So continuous execution manually or by the maximum sampling quantity that assignment procedure 60 is in advance carried out stops sampling until sampled whole shmoo figure or user.
More particularly, in case finish a stage of progressive uniform sampling, if in shmoo figure, find new feature, then restart adaptively sampled.If do not find new feature, then can carry out another stage of progressive uniform sampling, and process 60 can continue until the user stops this sampling or until in the shmoo figure that sampled have a few.
The below will provide the details of the specific part of process 60.
The example of operable progressive uniform sampling comprises that as above carrying out a grid with reference to minute sub of figure 6a to 6e and Fig. 7 a to 7c description samples in process 60, and such as G.Ramponi and S.Carrato at " An Adaptive Irregular Sampling Method for ProgressiveTransmission ", Preceeding International Conference on Image Processing, Vol.2, the described pseudo-Poisson dish (pseudo-poisson of 1998 pp.747-751, PPD) stochastic sampling, the content of the document is being hereby incorporated by reference, just as illustrating at this fully.For example, in one implementation, carry out stochastic sampling in the stage of 2.5% point in comprising shmoo figure, therefore, switching to adaptively sampled threshold percentage from progressive sampling is 6% point the shmoo figure.In non-shmoo figure situation, can carry out stochastic sampling in similar number percent data.The process 60 of utilizing the grid sampling to carry out is called as " progressive self-adaptation grid sampling ", and the process 60 of utilizing stochastic sampling to carry out is called as " progressive self-adapting random sampling ".
The interpolation that can be used for implementation 60 such as the traditional images interpolater of bilinear interpolation device and bicubic interpolater.In one implementation, this interpolater and bilinear interpolation device are similar, and similar with " An Adaptive Irregular Sampling Method for ProgressiveTransmission " middle four arest neighbors (4NN) interpolater of describing, quote the document as a reference at this.In this case, can be by being that eight gray levels (256 values) are carried out interpolation with the sample conversion among the shmoo figure.Before interpolation, be set to 255 and be not set to 0 by value by value.This interpolater centers on the increasing square region of the point of wanting interpolation until find that at least two sampled points operate by inspection.Then, according to these square interior two, three or four nearest sampled points, this interpolater carries out linear interpolation.If in square interior discovery additional sampled points, and this point to leave the distance of this interpolated point identical with the 4th, then in this interpolation, also utilize this point.
Because the adaptively sampled of shmoo figure pointed in theory near the tr pt in the shmoo figure, evaluator should carry out rim detection shmoo figure.For example 3 * 3Sobel wave filter or 3 * 3 gradient filters are measured as evaluator can to use traditional image to process edge detector.But, because shmoo figure's is simple in structure, measure more effective so discovery only will be used as evaluator by the value that interpolation obtains.Find that also because compare with using simple evaluator, 3 * 3 edge detectors can be sampled, so 3 * 3 edge detectors are so that can sample to the more multiple spot among the shmoo figure in the larger frequency band around this tr pt.
Because having, near the naming a person for a particular job edge of the tight sampling of requirement and pass through (255) or pass through (0) different value, so good based on the simple evaluator work of the interpolate value of putting.For twin-stage (bi-level) shmoo figure, can select evaluator threshold in case to depart from by or not by sampling greater than the point of 2.5% (gray-scale value is between 7 and 248), and the value outside this scope of not sampling.Gray level shmoo figure is more responsive to threshold level, therefore, in this case, adopt threshold value in case to depart from by or not by sampling greater than the point of 1% (gray-scale values between 3 and 252), be not positioned at value outside this scope and do not sample.Note that if shmoo figure is so complicated so that it is similar with the gray level photographs, then may need 3 * 3Sobel filtrator or gradient edge detector as evaluator preferably to sample near the edge in shmoo figure.
In one implementation, process 60 adopt adaptively sampled be included in sampling in the progressive grid sampling sub surpass evaluator measure have a few.The adaptively sampled at random selected element that is included in the grid, and if they surpass evaluator and measure then these points of sampling.Continue to carry out each adaptively sampled stage, until the point 2.5% or more is sampled, perhaps until the quantity of the candidate point of selecting at random above 16 times of always counting among the shmoo figure.The quantity of the candidate point that will consider in this stochastic sampling process limited preventing that adaptively sampled cost is long-time, but compare with the grid sampling, may cause so more at random uniform sampling and still less adaptively sampled.
Fig. 9 a to 9c illustrates and is performed to utilize progressive self-adaptation grid sampling to produce the result of process 60 of the shmoo figure of Fig. 1.O represents sampled point.Fig. 9 a illustrates and finishes the shmoo figure that produces behind the progressive uniform sampling, 7.4% the point of wherein having sampled.Fig. 9 b illustrates and finishes the shmoo figure that produces behind the adaptively sampled four-stage, 11.5% the point of wherein having sampled.Fig. 9 c illustrates the shmoo figure that finishes adaptively sampled rear generation, 19.7% the point of wherein having sampled.Shmoo figure shown in Fig. 9 c is basic identical with shmoo figure shown in Figure 1.
Figure 10 a to 10c illustrates and is performed to utilize progressive self-adapting random sampling to produce the result of process 60 of the shmoo figure of Fig. 1.As mentioned above, represent sampled point with O.Figure 10 a illustrates and finishes the shmoo figure that produces behind the progressive uniform sampling, 7.5% the point of wherein having sampled.Figure 10 b illustrates and finishes the shmoo figure that produces after progressive adaptively sampled two stages, 12.6% the point of wherein having sampled.Figure 10 c is illustrated in the shmoo figure that finishes progressive adaptively sampled rear generation, 25.1% the point of wherein having sampled.The shmoo figure of Figure 10 c is basic identical with the shmoo figure of Fig. 1.
In the example shown in Fig. 9 a to 9c and 10a and the 10b, in order to reproduce shmoo figure, the point of the shmoo figure upper 20% to 25% that in fact only needs to sample.
Figure 11 a to 11c illustrates and is performed to utilize progressive self-adaptation grid sampling to produce the result of process 60 of the shmoo figure of Fig. 2.As mentioned above, represent sampled point with O.Figure 11 a is illustrated in and finishes the shmoo figure that produces behind the progressive uniform sampling, 7.4% the point of wherein having sampled.Figure 11 b is illustrated in and finishes the shmoo figure that produces behind the adaptively sampled four-stage, 14.3% the point of wherein having sampled.Figure 11 c is illustrated in the shmoo figure that finishes progressive adaptively sampled rear generation, 28.8% the point of wherein having sampled.The shmoo figure of Figure 11 c is basic identical with the shmoo figure of Fig. 2.
Figure 12 a to 12c illustrates and is performed to utilize progressive self-adapting random sampling to produce the result of process 60 of the shmoo figure of Fig. 2.As mentioned above, represent sampled point with O.Figure 12 a is illustrated in and finishes the shmoo figure that produces behind the progressive uniform sampling, 7.5% the point of wherein having sampled.Figure 12 b is illustrated in and finishes the shmoo figure that produces behind the progressive adaptively sampled three phases, 15.1% the point of wherein having sampled.Figure 12 c is illustrated in the shmoo figure that finishes progressive adaptively sampled rear generation, 30.0% the point of wherein having sampled.The shmoo figure of Figure 12 c is basic identical with the shmoo figure of Fig. 2.
In the example shown in Figure 11 a to 11c and the 12a to 12c, in order to reproduce shmoo figure, 30% point among the shmoo figure that in fact only needs to sample.
Figure 13 a to 13f illustrates and is performed to utilize progressive self-adaptation grid sampling to produce the result of process 60 of the shmoo figure of Fig. 3.As mentioned above, represent sampled point with O.Figure 13 a is illustrated in and finishes the shmoo figure that produces behind the progressive uniform sampling, 6.25% the point of wherein having sampled.Figure 13 b illustrates the figure of the sampled point among Figure 13 a, wherein is shown as white with sampled point.Figure 13 c is illustrated in and finishes the shmoo figure that produces behind the adaptively sampled four-stage, 11.8% the point of wherein having sampled.Figure 13 d illustrates the figure of the sampled point among Figure 13 c.Figure 13 e is illustrated in the shmoo figure that finishes progressive adaptively sampled rear generation, 29.2% the point of wherein having sampled.This shmoo figure is basic identical with the original shmoo figure of Fig. 3.Figure 13 f illustrates the figure of the sampled point among Figure 13 e.
Figure 14 a to 14f illustrates and is performed to utilize progressive self-adapting random sampling to produce the result of process 60 of the shmoo figure of Fig. 3.As mentioned above, represent sampled point with O.Figure 14 a is illustrated in and finishes the shmoo figure that produces behind the progressive uniform sampling, 7.5% the point of wherein having sampled.Figure 14 b illustrates the figure (plot) of the sampled point among Figure 12 a, and wherein sampled point illustrates with white.Figure 14 c is illustrated in and finishes the shmoo figure that produces after two adaptively sampled stages, 12.5% the point of wherein having sampled.Figure 14 d illustrates the shmoo figure of the sampled point among Figure 14 c.Figure 14 e is illustrated in the shmoo figure that finishes progressive adaptively sampled rear generation, 35.0% the point of wherein having sampled.This shmoo figure basically original shmoo figure with Fig. 3 is identical.Figure 14 f illustrates the shmoo figure of the sampled point among Figure 14 e.
In the example shown in Figure 13 a to 13f and the 14a to 14f, in order to reproduce shmoo figure, in fact only need among the shmoo figure of sample graph 3 30% to 35% point.
One of advantage of process 60 is that it can not omit the little feature of shmoo figure usually.That is, process 60 by progressive sampling and adaptively sampled between alternately can continuous sampling shmoo figure until this shmoo figure that samples fully.For the ability of the little feature among this process discovery shmoo figure is described, the test shmoo figure that sampling is shown in Figure 15 is shown in Figure 16 a to 16c and 17a to 17c.
Figure 16 a to 16c illustrates and is performed to utilize progressive self-adaptation grid sampling to produce the result of process 60 of the shmoo figure of Figure 15.This shmoo figure that sampled 31.1% after, finish adaptively sampled.After this, restart progressive sampling, until find new feature, then restart adaptively sampled.In 62.2% the situation of sampling shmoo figure, find all features among the shmoo figure.
Specifically, Figure 16 a is illustrated in and finishes the shmoo figure that produces behind the progressive uniform sampling, 7.4% the point of wherein having sampled.Figure 16 b is illustrated in the shmoo figure that finishes adaptively sampled rear generation, 31.1% the point of wherein having sampled.Figure 16 c is illustrated in and finishes the shmoo figure that produces after the progressive and adaptively sampled additional phase, 62.2% the point of wherein having sampled.The shmoo figure of Figure 16 c is basic identical with the original shmoo figure of Figure 15.
Figure 17 a to 17c illustrates and is performed to utilize progressive self-adapting random sampling to produce the result of process 60 of the shmoo figure of Figure 15.This shmoo figure that sampled 35.1% after, adaptively sampled finishing.After this, restart progressive sampling, until find new feature, then restart adaptively sampled.In 45.1% the situation of sampling shmoo figure, can find all features among the shmoo figure.
Specifically, Figure 17 a is illustrated in and finishes the shmoo figure that produces behind the progressive uniform sampling, 7.5% the point of wherein having sampled.Figure 17 b is illustrated in the shmoo figure that finishes adaptively sampled rear generation, 35.1% the point of wherein having sampled.Figure 17 c is illustrated in and finishes the shmoo figure that produces after the progressive and adaptively sampled additional phase, 45.1% the point of wherein having sampled.The shmoo figure of Figure 15 c is basic identical with the original shmoo figure of Figure 13.
Utilize progressive adaptively sampled minimizing of shmoo figure to obtain the required time of shmoo figure.Therefore, software overhead will keep reduced levels.Will be by having the 2.8GHz Pentium of 1GByte RAM
4 processors, operation Windows
XP
Computing machine, for all the shmoo figure Survey Software expenses in this part.On average, the progressive and adaptively sampled expense based on grid is every 250 microseconds.On average, random progressive and adaptively sampled expense are every some 110ms.For the figure of shmoo as used herein, marked change does not occur with the size of shmoo figure or the shape of this shmoo figure in these times.
Given 10ms is to the typical shmoo point acquisition time of 100ms, then reduces the expense of offsetting by the software overhead of progressive adaptively sampled introducing greater than counting of obtaining of needs.V in Fig. 9 a to Fig. 9 c
OlIn the example of the progressive self-adaptation grid sampling of cycle shmoo figure, be in the 10ms situation at every some acquisition time, the sampling time of whole shmoo figure is about 10.89s.Utilize progressive self-adaptation grid 314 points of sampling, then acquisition time is about 3.22 seconds, approaches with respect to whole 1089 points on the sampling shmoo figure and saves for 70% time.Total software overhead in this case is about 78.5ms, and this is about 2.5% expense or approximately is equivalent to 8 additional points obtaining among this shmoo figure.Shmoo long for every some acquisition time or code optimization schemes, and it is less that this percentage can become.
The grid sampling is different with the advantage of stochastic sampling.The advantage of grid sampling comprises its simplicity and its less point of need to sampling.More particularly, sampling produces the figure of uniform sampling and does not have too large expense at regular intervals.In the shmoo example with simple structure of here describing, compare with adopting stochastic sampling, utilize the grid sampling to need the less point of sampling to reproduce original shmoo figure fully.
The advantage of stochastic sampling comprises the expense that needs are less.In some implementations, the required software overhead of stochastic sampling may be less than sample half of required software overhead of grid.
Example described here explanation is adopted progressively and adaptively sampled, and the time of shmoo can being schemed is with respect to the line by line sampling shortening 80% of whole shmoo figure.The progressive adaptively sampled low-definition version that can also be used for the user is shown fast shmoo figure.In the realization of describing, do not carry out the shape about shmoo figure feature here, the less feature among this shmoo figure can not omitted usually, and can carry out continuously adaptively sampled until this shmoo figure is finished sampling.
By computer program implementation 60 at least in part, this computer program namely is included in the computer program in the information carrier palpably, this information carrier is such as computer readable storage means or transmitting signal, this computer program is used for being carried out or being controlled by data processing equipment the operation of this data processing equipment, this data processing equipment such as programmable processor, computing machine or a plurality of computing machine.For example, can utilize computer control to be applied to the control signal of input switch 62 and output switch 64.
Computer program can be write with the programming language of the arbitrary form that comprises compiler language or interpretative code, and can be to comprise stand-alone program or module, parts, subroutine or to be suitable for the arbitrary form configuration of other unit of computing environment.Computer program can be configured to be positioned at a website or distributed a plurality of websites place and carrying out by a computing machine or a plurality of computing machine of network interconnection.
Can utilize one or more programmable processors of carrying out one or more computer program to carry out the action relevant with implementation procedure 60, with the function of execution calibration process.Utilize special purpose logic circuitry, for example, FPGA (field programmable gate array) and/or ASIC (special IC), can implementation 60 all or part of.
As an example, the processor that is fit to computer program comprises any one or a plurality of processor of general and special microprocessor and any type digital machine.Usually, processor is from ROM (read-only memory) or random access memory (RAM) or their the two reception instruction and datas.Computer components comprise for the processor of carrying out instruction and one or more memory device for the storage instruction and data.
Process 60 is not limited to progressive sampling described here and adaptively sampled use.Can adopt the progressive and adaptively sampled of any type.In addition, process 60 is not limited to shmoo figure and uses, but it can be used for data, the image of sample any type, such as grayscale image etc.
Can be with the factor combination of different embodiment described here together there not to be specifically described other embodiment above forming.There are not specifically described other embodiment within the scope of the appended claims at this yet.
Claims (8)
1. method that is used for obtaining the test data of measured device comprises:
By utilizing in parameter area first of progressive sampling to locate to test described device, obtain the first of described test data; And
Wherein, the described first that obtains described data comprises:
Carry out progressive sampling in described test data, to identify one group of first point;
Test described device at described group place at first, to produce the first test result; And
Utilize described the first test result to carry out interpolation with the interpolative data point;
Be identified in second point in the described parameter area based on described interpolative data point, described second point is selected from the interpolative data point that assessment tolerance surpasses predetermined threshold; And
Adaptively sampledly test described device at described second point place by utilizing, obtain the second portion of described test data.
2. method according to claim 1, wherein, obtain described first and further comprise:
Determine whether first quantity in the described group surpasses threshold value at first; And
If first quantity does not surpass described threshold value in described group, then repeat progressive sampling, test and carry out interpolation.
3. method according to claim 2 wherein, if first quantity surpasses described threshold value in described group, is then obtained described second portion, wherein, obtains described second portion and comprises:
Carry out described adaptively sampled, to identify one group of second point;
Second point place at described group tests described device, to produce the second test result; And
Utilize described the second test result to carry out interpolation to produce the described second portion of described test data.
4. method according to claim 3, wherein, obtain described second portion and further comprise:
Arrange and adaptively sampled relevant measuring;
Determine on described test data, whether to have and satisfy the described annex point of measuring;
Carry out adaptively sampled, with from described annex point identification another the group second point;
Test described device to produce additional the second test result at described another group second point place; And
Utilize described additional the second test result to carry out interpolation, to produce the part of described test data.
5. method according to claim 3 further comprises:
Specify the parameter of the described test data of definition, a plurality of points of described parameter-definition, described a plurality of points comprise described group and the group of described second point at first;
A plurality of points of a predetermined level is exceeded have been determined whether after tested; And
If also do not test a plurality of points of a predetermined level is exceeded, then by thirdly locating to test the third part that described device obtains described test data what utilize progressive sampling identification.
6. method according to claim 1 further comprises:
Utilize described first and the second portion of described test data to carry out interpolation, to obtain the disappearance part of described test data; And
Utilize described first and second portion and described disappearance part, show described test data.
7. method according to claim 1, wherein, described test data comprises the grid with the first peacekeeping second dimension, described the first dimension is corresponding to first parameter relevant with described device, and described second tie up corresponding to second parameter relevant with described device; And
Wherein, test comprises: obtain described the first parameter in the situation of given described the second parameter, perhaps obtain described the second parameter in the situation of given described the first parameter.
8. method according to claim 1, wherein, described device comprises semiconductor devices, and described test data is represented as shmoo figure.
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| PCT/US2006/029339 WO2007019077A2 (en) | 2005-08-04 | 2006-07-28 | Obtaining test data for a device |
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| US8279204B1 (en) * | 2005-12-22 | 2012-10-02 | The Mathworks, Inc. | Viewer for multi-dimensional data from a test environment |
| US8676188B2 (en) * | 2006-04-14 | 2014-03-18 | Litepoint Corporation | Apparatus, system and method for calibrating and verifying a wireless communication device |
| US8154308B2 (en) * | 2006-11-13 | 2012-04-10 | The Boeing Company | Method for characterizing integrated circuits for identification or security purposes |
| US20090119542A1 (en) * | 2007-11-05 | 2009-05-07 | Advantest Corporation | System, method, and program product for simulating test equipment |
| US8838819B2 (en) | 2009-04-17 | 2014-09-16 | Empirix Inc. | Method for embedding meta-commands in normal network packets |
| CN104678289A (en) * | 2015-02-13 | 2015-06-03 | 上海华岭集成电路技术股份有限公司 | Method for calibrating setting values and measurement values in shmoo test |
| US10108520B2 (en) * | 2015-10-27 | 2018-10-23 | Tata Consultancy Services Limited | Systems and methods for service demand based performance prediction with varying workloads |
| US10768230B2 (en) | 2016-05-27 | 2020-09-08 | International Business Machines Corporation | Built-in device testing of integrated circuits |
| US11733290B2 (en) | 2020-03-31 | 2023-08-22 | Advantest Corporation | Flexible sideband support systems and methods |
| US11619667B2 (en) * | 2020-03-31 | 2023-04-04 | Advantest Corporation | Enhanced loopback diagnostic systems and methods |
| US11829465B2 (en) * | 2020-10-22 | 2023-11-28 | Morphix, Inc. | Edge computing device with connector pin authentication for peripheral device |
| CN112865792B (en) * | 2021-01-08 | 2021-11-19 | 胜达克半导体科技(上海)有限公司 | Method for testing linearity of analog-digital converter at low cost |
| CN113075527A (en) * | 2021-02-23 | 2021-07-06 | 普赛微科技(杭州)有限公司 | Integrated circuit chip testing method, system and medium based on Shmoo test |
| WO2023090510A1 (en) * | 2021-11-18 | 2023-05-25 | 한국전자기술연구원 | Electronic device for performing data selection based on data supplementation condition, and executing method thereof |
| CN116773956A (en) * | 2022-03-08 | 2023-09-19 | 长鑫存储技术有限公司 | Data analysis method, device and storage medium |
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| JP5114404B2 (en) | 2013-01-09 |
| CN101501515A (en) | 2009-08-05 |
| WO2007019077A2 (en) | 2007-02-15 |
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| US7519878B2 (en) | 2009-04-14 |
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| EP1910856A2 (en) | 2008-04-16 |
| KR101264120B1 (en) | 2013-05-14 |
| TWI418826B (en) | 2013-12-11 |
| JP2009512000A (en) | 2009-03-19 |
| WO2007019077A3 (en) | 2008-11-13 |
| KR20080031921A (en) | 2008-04-11 |
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